In this episode, I sit down with Wendy Turner-Williams, a distinguished tech leader and executive with a deep history at companies like Microsoft and Salesforce. She's of the original minds behind what became Azure Data Factory, among other foundational tech. In this wide-ranging conversation, Wendy charts the trajectory from the early days of the Internet to the current AI-driven hype cycle and looming crisis. She explains how these tools of innovation are now being turned against the workforce and why this technological revolution is fundamentally more disruptive than anything that has come before. This episode is a candid, unfiltered discussion about the real-world impact of AI on jobs, the economy, and our collective future, and a call for leaders to act before it's too late. Timestamps: 00:22 - Catching up: The tough job market and writing new books. 05:49 - Wendy's impressive career history at Microsoft, Salesforce, and Tableau. 06:17 - The origin story of Azure Data Factory and other foundational projects at Microsoft. 09:18 - A personal story about the challenges of being a woman in Big Tech in the early days. 13:02 - A look back at a favorite early-career project: Digitizing physical maps with nascent GPS technology in 2001. 18:11 - The state of the tech industry: "Tech is cannibalizing itself because of AI." 20:31 - The massive, impending shock to the job market and why AI is different from previous industrial revolutions. 27:26 - Why the "human in the loop" is a temporary and misleading solution. 29:55 - Breaking down the numbers: The staggering quantity of white-collar jobs projected to be eliminated. 36:37 - Why leaders are failing to act and conversations are happening behind closed doors without solutions. 38:25 - Discussing potential solutions: Should companies have quotas for their human workforce? 45:21 - The need for "truth tellers" and leaders who are willing to question the current path and drive human-centric transformation. 53:15 - The grim reality for recent graduates with computer science degrees who can't find jobs. 56:22 - The risk of IP hoarding and engineers deliberately crippling systems to protect their jobs. 01:00:20 - Final thoughts: Are we waiting for a "let them eat cake" moment before we see real change?
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Here are 5 exciting and unique data analyst projects that will build your skills and impress hiring managers! These range from beginner to advanced and are designed to enhance your data storytelling abilities. ✨ Try Julius today at https://landadatajob.com/Julius-YT Where I Go To Find Datasets (as a data analyst) 👉 https://youtu.be/DHfuvMyBofE?si=ABsdUfzgG7Nsbl89 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator
⌚ TIMESTAMPS 00:00 - Introduction 00:24 - Project 1: Stock Price Analysis 03:46 - Project 2: Real Estate Data Analysis (SQL) 07:52 - Project 3: Personal Finance Dashboard (Tableau or Power BI) 11:20 - Project 4: Pokemon Analysis (Python) 14:16 - Project 5: Football Data Analysis (any tool)
🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Feeling behind on your data journey? Don't worry. Today, I'll list down the 13 signs that prove you're actually ahead (even if you're actually doing just some of these). ✨ Try Julius today at https://landadatajob.com/Julius-YT 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator ⌚ TIMESTAMPS 00:00 Introduction 00:05 #1 You can analyze data in Excel without panicking 00:52 #2 You know how to write basic SQL queries 01:17 #3 You can build a bar chart and scatter plot in Tableau or Power BI 01:59 #4 You can Google (or ChatGPT) your way through any error 02:45 #5 You can send me one portfolio project right now 03:45 #6 You talk about your data journey with friends and family regularly 05:50 #7 You’re actually applying to jobs (not just watching tutorials) 07:03 #8 You’ve joined a data community 07:48 #9 Your resume now includes (lots of) the right keywords 10:11 #10 You’ve optimized your LinkedIn for data roles 10:45 #11 A recruiter reaches out to you on LinkedIn 11:58 #12 You’ve had at least one real interview 12:52 #13 You’re comfortable not knowing everything (yet) 🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Jen Hawkins went from delivering pizzas to becoming a six-figure data analyst at a FAANG company in just 17 weeks. In our chat, she shares her Data Accelerator Program journey, how she used her background and new skills to stay motivated, land job offers, and eventually achieve her dream role. 💌 Join 10k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com/interviewsimulator Jen Hawkins' Confessions of an Accidental Delivery Driver: Tableau Supply Chain Project: ⌚ TIMESTAMPS 00:00 - Introduction 00:30 - The Struggles and Turning Points 07:49 - Transitioning to a Data Analyst Role 19:46 - Life as a Data Analyst at a FAANG Company 🔗 CONNECT WITH JEN: 🤝 LinkedIn: https://www.linkedin.com/in/jeandriska/ 🔗 CONNECT WITH AVERY 🎥 YouTube Channel: https://www.youtube.com/@averysmith 🤝 LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://instagram.com/datacareerjumpstart 🎵 TikTok: https://www.tiktok.com/@verydata 💻 Website: https://www.datacareerjumpstart.com/ Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Dashboards are everywhere in the data industry, but are they being used effectively? Many professionals find themselves creating dashboards that end up underutilized or misunderstood. The key is not just in the data presented, but in how it's communicated and used. How can you rethink your approach to dashboarding to ensure it aligns with business goals? What methods can you employ to engage users and drive meaningful actions? Lee is the President at DecisionViz, who provides training and consulting to organizations to improve their people, process, and culture around visualization and storytelling. He's a course creator for the University of Chicago, an instructor for TDWI, and an Adjunct Faculty Instructor for NYU School of Professional Studies. Lee is also a Tableau Certified Associate Consultant, 4 times Tableau Ambassador, and a long-term Tableau Partner. Previously, he was a Research Advisor for the International Institute of Analytics, the Founder of the 501c data community, and a senior manager at Nokia. In the episode, Richie and Lee explore the limitations of traditional dashboards, the importance of a product mindset in data visualization, the role of communication and standardization in analytics, the intersection of AI with dashboarding, and much more. Links Mentioned in the Show: DecisionVizConnect with LeeCourse: Understanding Data VisualizationRelated Episode: Data Storytelling and Visualization with Lea Pica from Present Beyond MeasureSign up to attend RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business
In this episode, you'll get to hear from former Tableau Product Manager Bethany Lyons about the importance of having product skills on data teams. Bethany talks us through her experience as a PM at one of the most well-known data companies in the world, and how she views the role of product skills on data teams. You'll leave with a better understanding of what Product teams do in an organization and how you can leverage your data skills to make a major impact. What You'll Learn: Why having product skills is so important on data teams Tips and tricks to bring product thinking into your data role Bethany's best advice for anyone pursuing a career in data Register for free to be part of the next live session: https://bit.ly/3XB3A8b
Follow us on Socials: LinkedIn YouTube Instagram (Mavens of Data) Instagram (Maven Analytics) TikTok Facebook Medium X/Twitter About our guest: Bethany Lyons has a passion for solving hard problems with data analytics, and believes that product management is the best way to advance this cause. Follow Bethany on LinkedIn
Help us become the #1 Data Podcast by leaving a rating & review! We are 67 reviews away! For anyone aiming to break into data analysis, Avery’s roadmap is the ultimate guide. With practical advice and clear steps, this episode sets you up for success in just 100 days. 💌 Join 30k+ aspiring data analysts & get my tips in your inbox weekly 👉 https://www.datacareerjumpstart.com/newsletter 🆘 Feeling stuck in your data journey? Come to my next free "How to Land Your First Data Job" training 👉 https://www.datacareerjumpstart.com/training 👩💻 Want to land a data job in less than 90 days? 👉 https://www.datacareerjumpstart.com/daa 👔 Ace The Interview with Confidence 👉 https://www.datacareerjumpstart.com//interviewsimulator ⌚ TIMESTAMPS 01:06 AI Avatars Talk About the Plan 02:04 Learning About Data Roles 03:55 Getting Good at Excel 04:55 Visualizing Data with Tableau 05:54 Learning SQL Basics 06:58 Starting Job Prep Early 07:15 Applying for Jobs Smartly 09:27 Capstone Project: Showing Off Your Skills 11:22 Last Tips and Encouragement 🔗 CONNECT WITH AVERY 🎥 YouTube Channel 🤝 LinkedIn 📸 Instagram 🎵 TikTok 💻 Website Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Doing sales better is perhaps the most direct route to making more revenue, so it should be a priority for every business. B2B sales is often very complex, with a mix of emails and video calls and prospects interacting with your website and social content. And you often have multiple people making decisions about a purchase. All this generates a massive data—or, more accurately, a mess of data—which very few sales teams manage to harness effectively. How can sales teams can make use of data, software, and AI to clean up this mess, work more effectively, and most of all, crush those quarterly targets? Ellie Fields is the Chief Product and Engineering Officer at Salesloft leading Product Management, Engineering, and Design. Ellie previously led development teams at Tableau responsible for product strategy and engineering for collaboration and mobile portfolio. Ellie also launched and led Tableau Public. In the episode Richie and Ellie explore the digital transformation of sales, how sales technology helps buyers and sellers, metrics for sales success, activity vs outcome metrics, predictive forecasting, AI, customizing sales processes, revenue orchestration, how data impacts sales and management, future trends in sales, and much more. Links Mentioned in the Show: SalesloftConnect with EllieForrester ResearchCourse - Understanding the EU AI ActRelated Episode: Data & AI at Tesco with Venkat Raghavan, Director of Analytics and Science at TescoRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile app Empower your business with world-class data and AI skills with DataCamp for business
Summary
Data lakehouse architectures have been gaining significant adoption. To accelerate adoption in the enterprise Microsoft has created the Fabric platform, based on their OneLake architecture. In this episode Dipti Borkar shares her experiences working on the product team at Fabric and explains the various use cases for the Fabric service.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management Data lakes are notoriously complex. For data engineers who battle to build and scale high quality data workflows on the data lake, Starburst is an end-to-end data lakehouse platform built on Trino, the query engine Apache Iceberg was designed for, with complete support for all table formats including Apache Iceberg, Hive, and Delta Lake. Trusted by teams of all sizes, including Comcast and Doordash. Want to see Starburst in action? Go to dataengineeringpodcast.com/starburst and get $500 in credits to try Starburst Galaxy today, the easiest and fastest way to get started using Trino. Your host is Tobias Macey and today I'm interviewing Dipti Borkar about her work on Microsoft Fabric and performing analytics on data withou
Interview
Introduction How did you get involved in the area of data management? Can you describe what Microsoft Fabric is and the story behind it? Data lakes in various forms have been gaining significant popularity as a unified interface to an organization's analytics. What are the motivating factors that you see for that trend? Microsoft has been investing heavily in open source in recent years, and the Fabric platform relies on several open components. What are the benefits of layering on top of existing technologies rather than building a fully custom solution?
What are the elements of Fabric that were engineered specifically for the service? What are the most interesting/complicated integration challenges?
How has your prior experience with Ahana and Presto informed your current work at Microsoft? AI plays a substantial role in the product. What are the benefits of embedding Copilot into the data engine?
What are the challenges in terms of safety and reliability?
What are the most interesting, innovative, or unexpected ways that you have seen the Fabric platform used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on data lakes generally, and Fabric specifically? When is Fabric the wrong choice? What do you have planned for the future of data lake analytics?
Contact Info
Parting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
Thank you for listening! Don't forget to check out our other shows. Podcast.init covers the Python language, its community, and the innovative ways it is being used. The Machine Learning Podcast helps you go from idea to production with machine learning. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you've learned something or tried out a project from the show then tell us about it! Email [email protected] with your story.
Links
Microsoft Fabric Ahana episode DB2 Distributed Spark Presto Azure Data MAD Landscape
Podcast Episode ML Podcast Episode
Tableau dbt Medallion Architecture Microsoft Onelake ORC Parquet Avro Delta Lake Iceberg
Podcast Episode
Hudi
Podcast Episode
Hadoop PowerBI
Podcast Episode
Velox Gluten Apache XTable GraphQL Formula 1 McLaren
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
Sponsored By:
Starburst: 
This episode is brought to you by Starburst - an end-to-end data lakehouse platform for data engineers who are battling to build and scale high quality data pipelines on the data lake. Powered by T
Driving impact with analytics goes beyond numbers and graphs; it's about telling a story that resonates. In this session, Brent Dykes, author of "Effective Data Storytelling" & the Founder & Chief Data Storyteller at AnalyticsHero, Lea Pica, author of "Present Beyond Measure" & the Founder at Story-driven by Data, and Andy Cotgreave, co-author of "The Big Book of Dashboards" and Senior Data Evangelist at Tableau, will unveil how to transform data into compelling narratives. They shed light on the art of blending analytics with storytelling, a key to making data-driven insights both understandable and influential within any organization.
In this episode of the Data Career Podcast, we include a variety of listener questions, shedding light on topics like the future of data engineering, requirements for becoming a data analyst, showcasing data cleaning proficiency in Excel, and securing data analyst internships.
Also discusses the significance of storytelling and views on Power BI versus Tableau & the impact of AI on data analysis roles.
Tune in now!
👍 Leave your review and download the bonus!
🤝 Ace your data analyst interview with the interview simulator
📩 Get my weekly email with helpful data career tips
📊 Come to my next free “How to Land Your First Data Job” training
🏫 Check out my 10-week data analytics bootcamp
Timestamps:
(02:10) - What’s the future of data engineering in 2024? (03:06) - Do you need a degree to become a data analyst? (04:57) - How to showcase Excel skills? (07:22) - How to land data analyst internships? (10:10) - What are the main technical skills required to land your first data job? (14:40) - Have you worked with many teachers looking to make a career transition? (16:24) - How to get a data analyst job for people with no work experience? (25:13) - Can you suggest SQL and Excel videos for data analysis? (28:46) - Do you think the data analysis industry is saturated? (28:21) - Do you find data analysts transferring to becoming a data scientist or a data engineer?
Connect with Avery:
📺 Subscribe on YouTube
🎙Listen to My Podcast
👔 Connect with me on LinkedIn
🎵 TikTok
Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Se você sonha em mergulhar no mundo dos dados, exploramos as estratégias e habilidades necessárias para trilhar o caminho de se tornar um cientista de dados em 2024. Descubra como se preparar para as oportunidades do futuro e dominar o universo da ciencia de dados!
Neste episódio do Data Hackers — a maior comunidade de AI e Data Science do Brasil-, conheçam essa dupla de especialistas:
Mikaeri Ohana — Líder de AI e ML na CI&T, Criadora de Conteúdo no Explica Mi, premiada pelo Google como Google Developer Expert em ML e pela Microsoft como Microsoft Most Valuable Professional em AI, mestranda na Unicamp e fundadora da Escola Tesseract. Nilton Ueda — Global Data Product Manager at @AB-Inbev/Ambev, Professor MBA FIAP/MACKENZIE/IMPACTA/IBMEC, @LATAM Tableau Ambassador 3x
Lembrando que você pode encontrar todos os podcasts da comunidade Data Hackers no Spotify, iTunes, Google Podcast, Castbox e muitas outras plataformas. Caso queira, você também pode ouvir o episódio aqui no post mesmo!
embed
Conheça nosso convidado:
Mikaeri Ohana Nilton Ueda
Bancada Data Hackers:
Paulo Vasconcellos Monique Femme Gabriel Lages
Falamos no episódioLinks de referências:
Participe e responda a pesquisa State of Data: http://www.stateofdata.com.br/podcast Onde encontrar a Mikaeri Http://Instagram.com/explicami https://medium.com/@mikaeriohana https://www.linkedin.com/in/mikaeriohana Onde encontrar o Nilton: https://www.linkedin.com/in/niltonkazuyukiueda/
Join me with Tableau expert Andy Kriebel about data visualization tips! 📊
Andy shares his expertise to help you level up your data skills, from creating purposeful dashboards to the power of dot maps.
Tune in now and take your data visualizations to the next level! 🎧
Connect with Andy Kriebel:
🤝 Connect on Linkedin
▶️ Subscribe to Youtube Channel
📔 Buy #MakeoverMonday Book
🎒 Learn About The Data School
🤝 Ace your data analyst interview with the interview simulator
📩 Get my weekly email with helpful data career tips
📊 Come to my next free “How to Land Your First Data Job” training
🏫 Check out my 10-week data analytics bootcamp
Timestamps:
(11:15) - When dealing with time series, your best friend is the versatile line chart 📈
(13:34) - Dive into dot maps for super-detailed visualizations 🌍
(17:30) Want to compare rankings over time? Bump chart!📊📈
(21:10) Keep your graphs simple and spiced up with context📉
(26:45) Dashboards should tell a story; ensure they have a purpose and context to keep folks engaged. 📋💡
(34:27) Prepping for an interview? Be chatty, be prepared with your interviewers. 🗣️🤝
Connect with Avery:
📺 Subscribe on YouTube
🎙Listen to My Podcast
👔 Connect with me on LinkedIn
🎵 TikTok
Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
🕵️♂️ Curious about the mysterious hiring process of a data career? Find out how Megan McGuire narrows down candidates and assesses skills in the podcast. Get insider knowledge on code assessments, interviews, and what it takes to land the dream data role! 💪📈
📊 Come to my next free “How to Land Your First Data Job” training
🏫 Check out my 10-week data analytics bootcamp
Timestamps:
(02:14) - The Value of Junior Analysts
(12:12) - Curiosity and Problem Solving in Data Analytics
(21:46) - Be the perfect candidate for specific company rather than a pretty good candidate
(24:15) - How drive, experience and upskilling set up interviewee success
(28:59) - Show off your skills with your Tableau Public or GitHub Profile
(36:53) - Rejections aren't necessarily your fault
Connect with Avery:
📺 Subscribe on YouTube
🎙Listen to My Podcast
👔 Connect with me on LinkedIn
🎵 TikTok
Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
You just learned SQL or Python, or Tableau. But you don’t know how to build your data science project? In this episode, Avery shares a 3-step guide to building your first data science project.
🌟 Join the data project club!
“25OFF” to get 25% off (first 50 members).
📊 Come to my next free “How to Land Your First Data Job” training
🏫 Check out my 10-week data analytics bootcamp
Timestamps:
(1:28) - Art is theft, and so is the data science project
(4:02) - Find ideas on Towards Data Science Medium
(5:32) - Read a few articles to get inspiration
(6:05) - Avery’s strategy is doing 30 projects in 30 days
(9:08) - How academia finds inspiration to write
(11:01) - Take Avery’s project, replicate and do it
Mentioned Links:
Building 30 Data Science Projects in 30 days: https://youtu.be/kKmA9ihIg20
30 Data Science Projects Resources: https://www.datacareerjumpstart.com/30projectsresourcesignup
I Used Data Science to UNCOVER McDonald’s Healthiest Meal: https://youtu.be/3bbFc1225-4
Connect with Avery:
📺 Subscribe on YouTube: https://www.youtube.com/c/AverySmithDataCareerJumpstart/videos 🎙Listen to My Podcast: https://podcasts.apple.com/us/podcast/data-career-podcast/id1547386535 👔 Connect with me on LinkedIn: https://www.linkedin.com/in/averyjsmith/ 📸 Instagram: https://www.instagram.com/datacareerjumpstart/ 🎵 TikTok: [https://www.tiktok.com/@verydata?]
Mentioned in this episode: Join the last cohort of 2025! The LAST cohort of The Data Analytics Accelerator for 2025 kicks off on Monday, December 8th and enrollment is officially open!
To celebrate the end of the year, we’re running a special End-of-Year Sale, where you’ll get: ✅ A discount on your enrollment 🎁 6 bonus gifts, including job listings, interview prep, AI tools + more
If your goal is to land a data job in 2026, this is your chance to get ahead of the competition and start strong.
👉 Join the December Cohort & Claim Your Bonuses: https://DataCareerJumpstart.com/daa https://www.datacareerjumpstart.com/daa
Understanding and interpreting data visualizations are one of the most important aspects of data literacy. When done well, data visualization ensures that stakeholders can quickly take away critical insights from data. Moreover, data visualization is often the best place to start when increasing organizational data literacy, as it’s often titled the “gateway drug” to more advanced data skills. Andy Cotgreave, Senior Data Evangelist at Tableau Software and co-author of The Big Book of Dashboards, joins the show to break down data visualization and storytelling, drawing from his 15-year career in the data space. Andy has spoken for events like SXSW, Visualized, and Tableau’s conferences and has inspired thousands of people to develop their data skills.
In this episode, we discuss why data visualization skills are so essential, how data visualization increases organizational data literacy, the best practices for visual storytelling, and much more.
This episode of DataFramed is a part of DataCamp’s Data Literacy Month, where we raise awareness about Data Literacy throughout September through webinars, workshops, and resources featuring thought leaders and subject matter experts that can help you build your data literacy, as well as your organization’s. For more information, visit: https://www.datacamp.com/data-literacy-month/for-teams
Hjalmar Gislason is the Founder and CEO of GRID.is, a BI notebook company that has been making big waves in the field in the last few years. He tells us all about GRID.is and the rise of data notebooks. In this episode, you'll learn: [0:05:50] Hjalmar explains exactly what a data notebook is and how it compares to other tools. [0:11:52] Reasons to consider using a data notebook along with a range of other tools. [0:27:30] The 'living' quality of the models that can be created on GRID. [0:33:28] A special offer for AOF from Hjalmar and how to sign up immediately! For full show notes, and the links mentioned visit: https://bibrainz.com/podcast/85 Enjoyed the Show? Please leave us a review on iTunes.
In this episode of DataFramed, we speak with Andy Cotgreave, Technical Evangelist at Tableau about the role of data storytelling when driving change with analytics, and the importance of the analyst role within a data-driven organization.
Throughout the episode, Andy discusses his background, the skills every analyst should know to equip organizations with better data-driven decision making, his best practices for data storytelling, how he thinks about data literacy and ways to spread it within the organization, the importance of community when creating a data-driven organization, and more.
Relevant links from the interview:
We’d love your feedback! Let us know which topics you’d like us to cover and what you think of DataFramed by answering this 30-second surveyCheck out our upcoming webinar with AndyCheck out Andy's bookBecome a Tableau expert
Summary Every data project, whether it’s analytics, machine learning, or AI, starts with the work of data cleaning. This is a critical step and benefits from being accessible to the domain experts. Trifacta is a platform for managing your data engineering workflow to make curating, cleaning, and preparing your information more approachable for everyone in the business. In this episode CEO Adam Wilson shares the story behind the business, discusses the myriad ways that data wrangling is performed across the business, and how the platform is architected to adapt to the ever-changing landscape of data management tools. This is a great conversation about how deliberate user experience and platform design can make a drastic difference in the amount of value that a business can provide to their customers.
Announcements
Hello and welcome to the Data Engineering Podcast, the show about modern data management You listen to this show to learn about all of the latest tools, patterns, and practices that power data engineering projects across every domain. Now there’s a book that captures the foundational lessons and principles that underly everything that you hear about here. I’m happy to announce I collected wisdom from the community to help you in your journey as a data engineer and worked with O’Reilly to publish it as 97 Things Every Data Engineer Should Know. Go to dataengineeringpodcast.com/97things today to get your copy! When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. With their managed Kubernetes platform it’s now even easier to deploy and scale your workflows, or try out the latest Helm charts from tools like Pulsar and Pachyderm. With simple pricing, fast networking, object storage, and worldwide data centers, you’ve got everything you need to run a bulletproof data platform. Go to dataengineeringpodcast.com/linode today and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Are you bored with writing scripts to move data into SaaS tools like Salesforce, Marketo, or Facebook Ads? Hightouch is the easiest way to sync data into the platforms that your business teams rely on. The data you’re looking for is already in your data warehouse and BI tools. Connect your warehouse to Hightouch, paste a SQL query, and use their visual mapper to specify how data should appear in your SaaS systems. No more scripts, just SQL. Supercharge your business teams with customer data using Hightouch for Reverse ETL today. Get started for free at dataengineeringpodcast.com/hightouch. Atlan is a collaborative workspace for data-driven teams, like Github for engineering or Figma for design teams. By acting as a virtual hub for data assets ranging from tables and dashboards to SQL snippets & code, Atlan enables teams to create a single source of truth for all their data assets, and collaborate across the modern data stack through deep integrations with tools like Snowflake, Slack, Looker and more. Go to dataengineeringpodcast.com/atlan today and sign up for a free trial. If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription Your host is Tobias Macey and today I’m interviewing Adam Wilson about Trifacta, a platform for modern data workers to assess quality, transform, and automate data pipelines
Interview
Introduction How did you get involved in the area of data management? Can you describe what Trifacta is and the story behind it? Across your site and material you focus on using the term "data wrangling". What is your personal definition of that term, and in what ways do you differentiate from ETL/ELT?
How does the deliberate use of that terminology influence the way that you think about the design and features of the Trifacta platform?
What is Trifacta’s role in the overall data platform/data lifecycle for an organization?
What are some examples of tools that Trifacta might replace? What tools or systems does Trifacta integrate with?
Who are the target end-users of the Trifacta platform and how do those personas direct the design and functionality? Can you describe how Trifacta is architected?
How have the goals and design of the system changed or evolved since you first began working on it?
Can you talk through the workflow and lifecycle of data as it traverses your platform, and the user interactions that drive it? How can data engineers share and encourage proper patterns for working with data assets with end-users across the organization? What are the limits of scale for volume and complexity of data assets that users are able to manage through Trifacta’s visual tools?
What are some strategies that you and your customers have found useful for pre-processing the information that enters your platform to increase the accessibility for end-users to self-serve?
What are the most interesting, innovative, or unexpected ways that you have seen Trifacta used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Trifacata? When is Trifacta the wrong choice? What do you have planned for the future of Trifacta?
Contact Info
LinkedIn @a_adam_wilson on Twitter
Parting Question
From your perspective, what is the biggest gap in the tooling or technology for data management today?
Closing Announcements
Thank you for listening! Don’t forget to check out our other show, Podcast.init to learn about the Python language, its community, and the innovative ways it is being used. Visit the site to subscribe to the show, sign up for the mailing list, and read the show notes. If you’ve learned something or tried out a project from the show then tell us about it! Email [email protected]) with your story. To help other people find the show please leave a review on iTunes and tell your friends and co-workers Join the community in the new Zulip chat workspace at dataengineeringpodcast.com/chat
Links
Trifacta Informatica UC Berkeley Stanford University Citadel
Podcast Episode
Stanford Data Wrangler DBT
Podcast Episode
Pig Databricks Sqoop Flume SPSS Tableau SDLC == Software Delivery Life-Cycle
The intro and outro music is from The Hug by The Freak Fandango Orchestra / CC BY-SA
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How to Make Stunning Data Visualizations: An interview with Roshaan Khan, a Tableau Savant, my frijend, and one of Tableau’s featured artists of 2020. We talk about data visualization, Tableau vs Power BI, the power of personal projects, and how Roshaan got started with data.
Connect with Roshaan on LinkedIn: https://www.linkedin.com/in/roshaankhan/
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